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Coverage hole alleviation using geographic routing for WSNs
Abstract
In this paper, we propose an algorithm to alleviate coverage hole problem using geographic routing strategy for wireless sensor networks (WSNs). In order to accomplish desired results, an optimal number of forwarder nodes is computed along with the selection of path that has minimum energy consumption. Moreover, at each hop residual energy of a sensor is calculated and knowledge up-to one hop neighbors of forwarder node that ensures the avoidance of energy hole problem. Simulations are conducted to validate that our claim of outperforming compared existing schemes in terms of packet delivery ratio (PDR) and energy dissipation of the network nodes.
... In order to mitigate the effects of node positioning in WSNs, several algorithms have been proposed [14], [15]. For instance, the energy condition mean squared error (ECMSE) [15] algorithm evaluates the position of the nodes by using geographic position knowledge. ...
The Internet of Things (IoT) has been a pivotal technology enabler for realizing smart cities' vision through the provision of connectivity for everyday objects by means of wireless sensor networks (WSNs). Scalability, flexibility, route efficiency, mobility support and reduced overhead in routing protocols are desired characteristics in large-scale WSNs. Given the several geographic routing schemes proposed, mainly focusing on positioning, location error, and energy consumption, still exhibit higher routing overhead and unbalanced energy consumption of sensor nodes which significantly affect the performance and lifetime of the network. In this paper, an energy-efficient geographic (EEG) routing protocol has been proposed that focuses on network throughput and energy consumption of sensor nodes. The proposed protocol applies mean square error algorithm to resolve the sensor localization problem. Moreover, routing overhead has been reduced by restricting the nodes to maintain single neighbor information. The proposed protocol reduces the energy holes in the network by efficiently balancing the energy consumption among sensor nodes. The extensive simulations illustrate that the proposed scheme manages energy consumption and packet delivery ratio (PDR) more efficiently in comparison to a state-of-the-art geographic routing protocol.
The routing of data packets in Wireless Sensor Networks(WSNs) is treated as one of the important aspects. The deadend phenomenon (also known as the "local maximum" problem) poses major difficulties when performing geographic forwarding in wireless sensor network since whenever a packet encounters a dead-end, additional overheads must be paid to forward the packet to the destination via alternative route. In this paper, the proposed algorithm route the data packets around the connectivity holes region. The proposed algorithm consists of two phases; the detection of dead node is performed in first phase, avoidance of connectivity holes and selection of forwarding nodes are performed in second phase of algorithm. The residual energy, packet delivery ratio and distance are considered while selecting forwarding nodes. The proposed algorithm ensures that the data packets are forwarded in an energy efficient manner and improves PDR. Through extensive experiments shows that our algorithm performs better than the existing Protocol [10] in terms of energy consumption, network life time, packet delivery ratio and energy consumed per packet.
Location-based routing protocols use position information for making packet forwarding decisions, assuming perfect location information. Unlike topological routing algorithms, they do not need to exchange and maintain routing information. They work nearly stateless. However, in practice there could be significant errors in obtaining location estimates.
In this paper, the impact of location errors on power consumption of these protocols will be analyzed via developing a mathematical model represents the location errors that may occur in real deployment. Then a simulation of the power consumption of two location-based routing protocols, Geographic Random Forwarding (GeRaf) and Minimum Energy Consumption Forwarding (MECF), is carried out to evaluate the mathematical model.
Both the obtained simulation results and the developed mathematical model show that this type of routing protocols suffers from substantial performance degradation in terms of power consumption in presence of location errors.
An effective transmission strategy plays a vital role in maximizing the lifetime of wireless sensor networks (WSNs). To fulfill such a maximization aim, an optimal-distance-based transmission strategy is put forward on the basis of ant colony optimization (ACO). First, by introducing two notions, most energy-efficient distance and most energy-balanced distance, a local optimal-distance achievement mechanism is presented not only for a high energy efficiency, but also a good energy balancing in WSNs. Furthermore, by working out a network lifetime evaluation method, a global optimal-distance acquirement scheme is developed to achieve energy depletion minimization for sensor nodes with maximal energy consumption throughout the network. Finally, it is proved by simulations that our findings significantly outperform the state-of-the-art solutions.
A focus of the scientific community is to design network oriented position-based routing protocols and this has resulted in a very high number of algorithms, different in approach and performance and each suited only to particular applications. However, though numerous, very few position-based algorithms have actually been adopted for commercial purposes. This article is a survey of almost 50 position-based routing protocols and it comes as an aid in the implementation of this type of routing in various applications which may need to consider the advantages and pitfalls of position-based routing. An emphasis is made on geographic routing, whose notion is clarified as a more restrictive and more efficient type of position-based routing. The protocols are therefore divided into geographic and non-geographic routing protocols and each is characterized according to a number of network design issues and presented in a comparative manner from multiple points of view. The main requirements of current general applications are also studied and, depending on these, the survey proposes a number of protocols for use in particular application areas. This aims to help both researchers and potential users assess and choose the protocol best suited to their interest.
This paper proposes a non-uniform solution to the energy hole problem. The network is formed by a large number of tiny sensors, randomly scattered over a circular area and the sink positioned at the center. The sensors produce data with the same rate and the data travels from the nodes to the sink in a multi-hop fashion, using a shortest path routing. The basic idea, in order to avoid the energy hole around the sink, is to equip each network area with so much energy as the traffic load of that area. Firstly, a pure analytical expression for the traffic load is derived and then, based on this expression, a non-uniform deployment is proposed, with variable surface density, for a certain number of dormant nodes. Each time an active node exhaust its battery, a near dormant node becomes active and takes its place. The proposed strategy improves the network lifetime by a factor of 50 and the energy utilization by a factor of 6, compared to a conventional network without dormant nodes.
Planning of energy-efficient protocols is critical for Wireless Sensor Networks (WSNs) because of the constraints on the sensor nodes' energy. The routing protocol should be able to provide uniform power dissipation during transmission to the sink node. In this paper, we present a self-optimization scheme for WSNs which is able to utilize and optimize the sensor nodes' resources, especially the batteries, to achieve balanced energy consumption across all sensor nodes. This method is based on the Ant Colony Optimization (ACO) metaheuristic which is adopted to enhance the paths with the best quality function. The assessment of this function depends on multi-criteria metrics such as the minimum residual battery power, hop count and average energy of both route and network. This method also distributes the traffic load of sensor nodes throughout the WSN leading to reduced energy usage, extended network life time and reduced packet loss. Simulation results show that our scheme performs much better than the Energy Efficient Ant-Based Routing (EEABR) in terms of energy consumption, balancing and efficiency.
Geographic routing in wireless sensor networks is based on the prerequisite that every node has information about its current position, for instance via GPS or some localization algorithm. This location information has a certain degree of inaccuracy in real deployments. The majority of geographic routing algorithms, however, has been designed for nodes with exact position information. We show that location errors yield bad performance or even complete failures. Two elaborated geographic routing algorithms for sensor networks, GPSR and BGR, are evaluated with the nodes having inaccurate location information, varying the standard deviation of the position error between zero and the transmission range. Simulation studies show a vast decrease of the packet delivery ratio. To enhance both algorithms, fixes for them are presented to improve the delivery ratio and to save energy in case of location errors.
Recently, geographic routing in wireless networks has gained attention due to several advantages of location information. Location information eliminates the necessity to set up and maintain explicit routes. These advantages allow scalability especially in dynamic and unstable wireless networks. However, no matter which technologies or techniques a location system uses, its measurements will have some amount of quantifiable inaccuracy depending on environment and system. These inaccuracies may affect the performance and even correctness of geographic routing. However, thus far, these impacts have not been studied in-depth. In this paper, we analyze the impact of location inaccuracy on geographic routing. Our study shows the significant impact of location inaccuracy on the performance of geographic routing in terms of packet drops, non-optimal paths and routing loops.
In this paper, we propose a new geographic routing algorithm that alleviates the effect of location errors on routing in wireless ad hoc networks. In most previous work, geographic routing has been studied assuming perfect location information. However, in practice there could be significant errors in obtaining location estimates, even when nodes use GPS, hence existing geographic routing schemes will need to be appropriately modified. We investigate how such location errors affect the performance of geographic routing strategies. We incorporate location errors into our objective function by considering both transmission failures and backward progress. Each node then forwards packets to the node that maximizes this objective function. We call this strategy Maximum Expectation within transmission Range (MER). Simulation results with MER show that accounting for location errors significantly improves the performance of geographic routing. Our analysis also shows that our algorithm works well up to a critical threshold of error. We also show that MER is robust to the location error model and model parameters. Further, via simulations, we show that in a mobile environment MER performs better than existing approaches.
Network lifetime is a crucial performance metric to evaluate data-gathering wireless sensor networks (WSNs) where battery-powered sensor nodes periodically sense the environment and forward collected samples to a sink node. In this paper, we propose an analytic model to estimate the entire network lifetime from network initialization until it is completely disabled, and determine the boundary of energy hole in a data-gathering WSN. Specifically, we theoretically estimate the traffic load, energy consumption, and lifetime of sensor nodes during the entire network lifetime. Furthermore, we investigate the temporal and spatial evolution of energy hole and apply our analytical results to WSN routing in order to balance the energy consumption and improve the network lifetime. Extensive simulation results are provided to demonstrate the validity of the proposed analytic model in estimating the network lifetime and energy hole evolution process.
Many consumer products in the home environment are managed by the Wireless Sensor Networks (WSNs). However, the energy hole problem in the WSNs which with logical ring topology and uniformly distributed sensors is usually caused by the energy exhaustion of the sensors which distributed in the first radius range of the sink. This paper firstly analyzed the energy consumption model of the sensor, the data transmission model of the sensor, and the energy consumption distribution model of the WSNs. Then, a WSN Energy Hole Alleviating (WSNEHA) algorithm, which is based on the data forwarding and router selection strategy, is proposed. The WSNEHPA adopts the data forwarding and routing selection strategy to balance the energy consumption of the sensors in the first radius range of the sink. Experimental results demonstrate that WSNEHPA can efficiently balance the energy consumption of the sensors in the first radius range of the sink, and that the lifetime of the WSNs can be extended efficiently.
In Wireless Sensor Networks (WSNs), Sensor nodes (nodes) are equipped with limited energy source. Therefore, efficient energy utilization of nodes has become a hot research area in WSNs. In this paper, we introduce a new routing technique for WSNs in which, we solve the problem of unbalanced energy utilization, which causes energy and coverage holes in WSNs. Deployment area is divided into subareas; each subarea logically represents a static cluster. Dividing network field into subfields helps to control coverage hole problem whereas, static clustering helps to avoid energy hole problem. Mathematical formulation of the proposed work is provided to analyse and verify our technique. Simulation results show that our technique balances energy utilization of the network.
Realistic geographic routing algorithms need to ensure quality of services in wireless sensor network applications while being resilient to the inherent localization errors of positioning algorithms. A number of solutions robust against location errors have been proposed in the literature and their design focuses either on a high throughput or on a balanced energy consumption. Ideally, both aspects need to be addressed by the same algorithm, but in most cases, the proposed routing techniques compromise between the two. The present work aims to minimize such a tradeoff and to facilitate a higher packet delivery ratio than similar geographic routing techniques, while still being energy efficient. This is achieved through a novel proposal entitled energy conditioned mean square error algorithm (ECMSE), which makes use of statistical assumptions of Gaussianly distributed location error and Ricianly distributed distances between sensor nodes. In addition, it makes use of an energy efficient feature, which includes information about the energy cost of the forwarding decision. By using a location-error-resilient and distance-based power metric, the ECMSE provides an improved performance in realistic simulations in comparison with other error-coping geographic routing algorithms.
One major limitation in a Wireless Sensor Network (WSN) is the energy dissipation of the nodes and the lifetime of the node's battery. The traffic in a sensor network follows a many-to one pattern, where nodes nearer to the sink carry heavier traffic loads. Therefore, the nodes around the sink would deplete their energy faster, leading to what is known as an energy hole around the sink. The aim of this paper is to overcome the power constraints in WSN by wirelessly charging the nodes. We investigate both theoretically and through simulations whether the physical phenomenon of long-lifetime resonant electromagnetic states with localized slowly-evanescent field patterns can be used to transfer energy efficiently over multiple hops. We specify the hardware the modified sensor node needs in order to wirelessly transmit and receive energy and introduce a new layer called the charging layer into the sensor network protocol stack. Our results show that multi-hop wireless energy transfer can be done with an efficiency as high as 20% over 8 hops. The work in this paper is the first that addresses multi-hop wireless energy transfer in sensor networks and is the building block for our and other future research in this area.
Existing energy-efficient geographic routing algorithms have been shown to reduce energy consumption and hence prolong the lifetime of multi-hop wireless networks. However, in practical deployment scenarios, where location errors inevitably exist, these algorithms are vulnerable to a substantial performance degradation not only in terms of packet delivery ratio but also energy consumption. This paper focuses on the fundamental impact of localization errors in the design of energy-efficient geographic routing algorithms. First, we analyze the properties of existing energy-efficient geographic routing algorithms. This is then extended to compare these energy-efficient geographical routing algorithms in the presence of localization errors. The main contribution of this section is an in-depth analysis of the impact of location errors on geographic routing in terms of energy efficiency. By incorporating location error statistics into an objective function, we propose a new energy-efficient geographic routing algorithm named LED. An adaptive transmission strategy is then proposed to cope with the transmission failure caused by location errors. Finally, extensive performance evaluations show that our proposal is robust to location errors, thus statistically minimizing consumed transmit power as a packet is relayed from source to destination.
Recent advances in wireless sensor networks have led to many new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. This paper surveys recent routing protocols for sensor networks and presents a classification for the various approaches pursued. The three main categories explored in this paper are data-centric, hierarchical and location-based. Each routing protocol is described and discussed under the appropriate category. Moreover, protocols using contemporary methodologies such as network flow and quality of service modeling are also discussed. The paper concludes with open research issues.
A wireless sensor network (WSN) has important applications such as remote environmental monitoring and target tracking. This has been enabled by the availability, particularly in recent years, of sensors that are smaller, cheaper, and intelligent. These sensors are equipped with wireless interfaces with which they can communicate with one another to form a network. The design of a WSN depends significantly on the application, and it must consider factors such as the environment, the application’s design objectives, cost, hardware, and system constraints. The goal of our survey is to present a comprehensive review of the recent literature since the publication of [I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, A survey on sensor networks, IEEE Communications Magazine, 2002]. Following a top-down approach, we give an overview of several new applications and then review the literature on various aspects of WSNs. We classify the problems into three different categories: (1) internal platform and underlying operating system, (2) communication protocol stack, and (3) network services, provisioning, and deployment. We review the major development in these three categories and outline new challenges.
We propose a new link metric called normalized advance (NADV) for geographic routing in multihop wireless networks. NADV selects neighbors with the optimal trade-off between proximity and link cost. Coupled with the local next hop decision in geographic routing, NADV enables an adaptive and efficient cost-aware routing strategy. Depending on the objective or message priority, applications can use the NADV framework to minimize various types of link cost.We present efficient methods for link cost estimation and perform detailed experiments in simulated environments. Our results show that NADV outperforms current schemes in many aspects: for example, in high noise environments with frequent packet losses, the use of NADV leads to 81% higher delivery ratio. When compared to centralized routing under certain settings, geographic routing using NADV finds paths whose cost is close to the optimum. We also conducted experiments in Emulab testbed and the results demonstrate that our proposed approach performs well in practice.
Geographic routing is one of the most suitable routing strategies for large scale wireless sensor networks due to its low overhead and high scalability features. A geographic routing scheme usually combines a geographic greedy forwarding with a recovery mechanism to solve the local minima problem. Solutions proposed in the literature commonly combine greedy forwarding with the well known face routing for achieving this goal. However, the average path length in number of hops produced by face routing could be much worse than the optimal topological path in most realistic scenarios. In this paper, we propose a new intermediate procedure between the geographic greedy mode and the recovery mode in order to improve routing efficiency in number of hops, without network overhead. It exploits the optimal topological route to base stations, obtained by beacon messages, as a resource to find better routes than the ones created by face routing. We show by simulations that the proposed hybrid approach leads to a significant improvement of routing performance when applied to combined greedy-face routing algorithms.
Geographic routing has been studied as an attractive approach due to its simplicity and scalability properties in routing for wireless ad hoc networks. Greedy routing is an important component of many geographic routing protocols which use a combined routing approach; a kind of recovery routing is used in case that greedy routing is impossible. In this paper, we propose the stateless extension of greedy routing called GR(k) that implements a k-bound forwarding algorithm where the parameter k controls the routing success rate and the corresponding overhead. We design three k-bound forwarding algorithms and evaluate which one is best via extensive simulation. The proposed approach improves the success rate of greedy routing by 20–40% at low node densities but in low overhead. These improvements mitigate the adverse effect of recovery routing (e.g. face routing) because the use of recovery routing is minimized; In particular, using GR(k) instead of greedy routing can reduce the number of packet transmissions up to 50%. We show that GR(k) is effective in reducing the average hop stretch in geographic routing by at most 30%.
Static always-on wireless sensor networks (WSNs) are affected by the energy sink-hole problem, where sensors nearer a central gathering node, called the sink, suffer from significant depletion of their battery power (or energy). It has been shown through analysis and simulation that it is impossible to guarantee uniform energy depletion of all the sensors in static uniformly distributed always-on WSNs with constant data reporting to the sink when the sensors use their nominal communication range to transmit data to the sink. We prove that the energy sink-hole problem can be solved provided that the sensors adjust their communication ranges. This solution, however, imposes a severe restriction on the size of a sensor field. To overcome this limitation, we propose a sensor deployment strategy based on energy heterogeneity with a goal that all the sensors deplete their energy at the same time. Simulation results show that such a deployment strategy helps achieve this goal. To solve the energy sink-hole problem for homogeneous WSNs, we propose a localized energy-aware-Voronoi-diagram-based data forwarding (EVEN) protocol. EVEN combines sink mobility with a new concept, called energy-aware Voronoi diagram. Through simulations, we show that EVEN outperforms similar greedy geographical data forwarding protocols and has performance that is comparable to that of an existing data collection protocol that uses a joint mobility and routing strategy. Precisely, we find that EVEN yields an improvement of more than 430 percent in terms of network lifetime.
A cost aware metric for wireless networks based on remaining battery power at nodes was proposed for shortest-cost routing algorithms, assuming constant transmission power. Power-aware metrics, where transmission power depends on distance between nodes and corresponding shortest power algorithms were also proposed. We define a power-cost metric based on the combination of both node's lifetime and distance-based power metrics. We investigate some properties of power adjusted transmissions and show that, if additional nodes can be placed at desired locations between two nodes at distance d, the transmission power can be made linear in d as opposed to d<sup>α</sup> dependence for α ⩾ 2. This provides basis for power, cost, and power-cost localized routing algorithms where nodes make routing decisions solely on the basis, of location of their neighbors and destination. The power-aware routing algorithm attempts to minimize the total power needed to route a message between a source and a destination. The cost-aware routing algorithm is aimed at extending the battery's worst-case lifetime at each node. The combined power-cost localized routing algorithm attempts to minimize the total power needed and to avoid nodes with a short battery's remaining lifetime. We prove that the proposed localized power, cost, and power-cost efficient routing algorithms are loop-free and show their efficiency by experiments